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      Genetic censusing identifies an unexpectedly sizeable population of an endangered large mammal in a fragmented forest landscape

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          Abstract

          Background

          As habitat degradation and fragmentation continue to impact wildlife populations around the world, it is critical to understand the behavioral flexibility of species in these environments. In Uganda, the mostly unprotected forest fragment landscape between the Budongo and Bugoma Forests is a potential corridor for chimpanzees, yet little is known about the status of chimpanzee populations in these fragments.

          Results

          From 2011 through 2013, we noninvasively collected 865 chimpanzee fecal samples across 633 km 2 and successfully genotyped 662 (77%) at up to 14 microsatellite loci. These genotypes corresponded to 182 chimpanzees, with a mean of 3.5 captures per individual. We obtained population size estimates of 256 (95% confidence interval 246–321) and 319 (288–357) chimpanzees using capture-with-replacement and spatially explicit capture–recapture models, respectively. The spatial clustering of associated genotypes suggests the presence of at least nine communities containing a minimum of 8–33 individuals each. Putative community distributions defined by the locations of associated genotypes correspond well with the distribution of 14 Y-chromosome haplotypes.

          Conclusions

          These census figures are more than three times greater than a previous estimate based on an extrapolation from small-scale nest count surveys that tend to underestimate population size. The distribution of genotype clusters and Y-chromosome haplotypes together indicate the presence of numerous male philopatric chimpanzee communities throughout the corridor habitat. Our findings demonstrate that, despite extensive habitat loss and fragmentation, chimpanzees remain widely distributed and exhibit distinct community home ranges. Our results further imply that elusive and rare species may adapt to degraded habitats more successfully than previously believed. Their long-term persistence is unlikely, however, if protection is not afforded to them and habitat loss continues unabated.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s12898-015-0052-x) contains supplementary material, which is available to authorized users.

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          Most cited references140

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          R: A Language and Environment for Statistical Computing.

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            Spatially explicit maximum likelihood methods for capture-recapture studies.

            Live-trapping capture-recapture studies of animal populations with fixed trap locations inevitably have a spatial component: animals close to traps are more likely to be caught than those far away. This is not addressed in conventional closed-population estimates of abundance and without the spatial component, rigorous estimates of density cannot be obtained. We propose new, flexible capture-recapture models that use the capture locations to estimate animal locations and spatially referenced capture probability. The models are likelihood-based and hence allow use of Akaike's information criterion or other likelihood-based methods of model selection. Density is an explicit parameter, and the evaluation of its dependence on spatial or temporal covariates is therefore straightforward. Additional (nonspatial) variation in capture probability may be modeled as in conventional capture-recapture. The method is tested by simulation, using a model in which capture probability depends only on location relative to traps. Point estimators are found to be unbiased and standard error estimators almost unbiased. The method is used to estimate the density of Red-eyed Vireos (Vireo olivaceus) from mist-netting data from the Patuxent Research Refuge, Maryland, U.S.A. Estimates agree well with those from an existing spatially explicit method based on inverse prediction. A variety of additional spatially explicit models are fitted; these include models with temporal stratification, behavioral response, and heterogeneous animal home ranges.
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              Noninvasive genetic sampling: look before you leap.

              Noninvasive sampling allows genetic studies of free-ranging animals without the need to capture or even observe them, and thus allows questions to be addressed that cannot be answered using conventional methods. Initially, this sampling strategy promised to exploit fully the existing DNA-based technology for studies in ethology, conservation biology and population genetics. However, recent work now indicates the need for a more cautious approach, which includes quantifying the genotyping error rate. Despite this, many of the difficulties of noninvasive sampling will probably be overcome with improved methodology.
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                Author and article information

                Contributors
                msmccart@usc.edu
                jack_lester@eva.mpg.de
                ejh20@st-andrews.ac.uk
                arandjel@eva.mpg.de
                stanford@usc.edu
                vigilant@eva.mpg.de
                Journal
                BMC Ecol
                BMC Ecol
                BMC Ecology
                BioMed Central (London )
                1472-6785
                25 August 2015
                25 August 2015
                2015
                : 15
                : 21
                Affiliations
                [ ]Department of Biological Sciences, Dana and David Dornsife College of Letters, Arts, and Sciences, University of Southern California, 3616 Trousdale Parkway, AHF 107, Los Angeles, CA 90089-0371 USA
                [ ]Max Planck Institute for Evolutionary Anthropology, Deutscher Platz 6, 04103 Leipzig, Germany
                [ ]Centre for Research into Ecological and Environmental Modelling, The Observatory, Buchanan Gardens, University of St Andrews, Fife, KY16 9LZ UK
                Article
                52
                10.1186/s12898-015-0052-x
                4549125
                26303656
                dc4d1968-0fb8-49ec-8c15-856666f22786
                © McCarthy et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 9 July 2015
                : 15 July 2015
                Categories
                Research Article
                Custom metadata
                © The Author(s) 2015

                Ecology
                habitat fragmentation,genetic census,ecological corridor,chimpanzee,population estimate,pan troglodytes,mark recapture

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